Monte Carlo event generator validation and tuning for the LHC

We summarise the motivation for, and the status of, the tools developed by CEDAR/MCnet for validating and tuning Monte Carlo event generators for the LHC against data from previous colliders. We then present selected preliminary results from studies of event shapes and hadronisation observables from e+e- colliders, and of minimum bias and underlying event observables from the Tevatron, and comment on the approach needed with early LHC data to best exploit the potential for new physics discoveries at the LHC in the next few years.Comment: Prepared for Proceedings of XII Advanced Computing and Analysis Techniques in Physics Research, November 3-7 2008, Erice, Ital

New developments in event generator tuning techniques

Data analyses in hadron collider physics depend on background simulations performed by Monte Carlo (MC) event generators. However, calculational limitations and non-perturbative effects require approximate models with adjustable parameters. In fact, we need to simultaneously tune many phenomenological parameters in a high-dimensional parameter-space in order to make the MC generator predictions fit the data. It is desirable to achieve this goal without spending too much time or computing resources iterating parameter settings and comparing the same set of plots over and over again. We present extensions and improvements to the MC tuning system, Professor, which addresses the aforementioned problems by constructing a fast analytic model of a MC generator which can then be easily fitted to data. Using this procedure it is for the first time possible to get a robust estimate of the uncertainty of generator tunings. Furthermore, we can use these uncertainty estimates to study the effect of new (pseudo-) data on the quality of tunings and therefore decide if a measurement is worthwhile in the prospect of generator tuning. The potential of the Professor method outside the MC tuning area is presented as well.Comment: To appear in the proceedings of the 13th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, ACAT2010, Jaipur, India, February 22-27, 201

Systematic event generator tuning for the LHC

In this article we describe Professor, a new program for tuning model parameters of Monte Carlo event generators to experimental data by parameterising the per-bin generator response to parameter variations and numerically optimising the parameterised behaviour. Simulated experimental analysis data is obtained using the Rivet analysis toolkit. This paper presents the Professor procedure and implementation, illustrated with the application of the method to tunes of the Pythia 6 event generator to data from the LEP/SLD and Tevatron experiments. These tunes are substantial improvements on existing standard choices, and are recommended as base tunes for LHC experiments, to be themselves systematically improved upon when early LHC data is available.Comment: 28 pages. Submitted to European Physical Journal C. Program sources and extra information are available from http://projects.hepforge.org/professor

Systematic improvement of QCD parton showers

In this contribution, we will give a brief overview of the progress that has been achieved in the field of combining matrix elements and parton showers. We exemplify this by focusing on the case of electron--positron collisions and by reporting on recent developments as accomplished within the Sherpa event generation framework.Comment: 6 figures, to appear in the proceedings of Linear Collider 2011 (Understanding QCD at linear colliders in searching for old and new physics), 12--16 September 2011, ECT*, Trento, Ital